关键词: 显著性检测, 图像分块, HSV颜色空间, 纹理特征, 目标检测

Abstract: Visual saliency detection has very important applications in many aspects such as image segmentation, adaptive compression and object recognition. This paper presents a saliency detection algorithm based on HSV color, texture and spatial position. By this method, the image is divided into small pieces in order to get the local information of the image, and color saliency map is computed in combination with the images’color uniqueness and spatial distribution to compute color saliency map. At the same time, the paper uses Gabor filters at different scales and directions to get the texture feature vector, and then calculates the difference of texture feature vectors to get the texture saliency map. Finally, the combination of the two gets a final saliency map. The experimental results show that this method can get satisfactory results in terms of detection and noise immunity, etc.

Key words: saliency detection, image block, HSV color space, texture feature, target detection